0.1_model

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.6384
• Accuracy: 0.6570

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 128
• eval_batch_size: 128
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	20	0.6763	0.5704
No log	2.0	40	0.6649	0.5812
No log	3.0	60	0.6591	0.6318
No log	4.0	80	0.6364	0.6534
No log	5.0	100	0.6366	0.6462
No log	6.0	120	0.6776	0.6282
No log	7.0	140	0.6384	0.6570
No log	8.0	160	0.6612	0.6282
No log	9.0	180	0.6645	0.6390
No log	10.0	200	0.6765	0.6354

Framework versions

• Transformers 4.50.3
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1